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Factory Connection Jobs in Texas (NOW HIRING)

Collaborate with the Store Director to act as a shared business owner with a meaningful connection ... Crew Factory, and Madewell * Competitive Paid Time Off (PTO) plan, including paid holidays * 401(k) ...

Collaborate with the Store Director to act as a shared business owner with a meaningful connection ... Crew Factory, and Madewell * Competitive Paid Time Off (PTO) plan, including paid holidays * 401(k) ...

Lead your team & drive your business with a meaningful connection to every aspect of the brand ... Crew Factory, and Madewell * Competitive Paid Time Off (PTO) plan, including paid holidays * 401(k) ...

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Factory Connection information

See Texas salary details

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How much do factory connection jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for factory connection in Texas is $15.71, according to ZipRecruiter salary data. Most workers in this role earn between $14.33 and $16.78 per hour, depending on experience, location, and employer.

What types of collaboration are common for a Factory Connection role within a manufacturing facility?

Factory Connection professionals often serve as key links between production teams, supervisors, and logistics or supply chain departments. They coordinate closely with line workers to monitor output and address any production issues, while also relaying important updates to management and ensuring materials or parts are delivered on time. Daily responsibilities may include facilitating team meetings, updating workflow status, and troubleshooting operational bottlenecks. This collaborative approach helps maintain efficient production schedules and supports the overall success of the manufacturing operation.

What are the key skills and qualifications needed to thrive in the Factory Connection position, and why are they important?

To excel as a Factory Connection, you need strong communication skills, attention to detail, and a basic understanding of manufacturing or distribution operations. Familiarity with production scheduling software, supply chain management tools, and inventory tracking systems is often required. Teamwork, problem-solving abilities, and adaptability are valuable soft skills for this role. These qualities are crucial for maintaining efficient workflow, ensuring accurate information relay, and supporting seamless operations within a factory environment.

What is a Factory Connection job?

A Factory Connection job typically involves working in a retail environment, assisting customers, managing inventory, and maintaining store operations. Employees may handle merchandising, stocking, cashiering, and providing customer service. Positions vary from sales associates to management roles, offering opportunities for career growth. Factory Connection specializes in affordable fashion, so employees often help customers find stylish clothing at budget-friendly prices.

What jobs make $3,000 a month without a degree?

Factory connection roles such as skilled machine operators, maintenance technicians, or quality control inspectors can sometimes earn around $3,000 monthly without a degree, especially with experience and certifications. Other options include sales positions, certain transportation jobs like truck driving, or skilled trades such as welding, which may require vocational training but not a formal degree.
What are popular job titles related to Factory Connection jobs in Texas? For Factory Connection jobs in Texas, the most frequently searched job titles are:
What cities in Texas are hiring for Factory Connection jobs? Cities in Texas with the most Factory Connection job openings:
Infographic showing various Factory Connection job openings in Texas as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $32,677 per year, or $15.7 per hour.
AI Engineer AI Modernization Factory-VS Code & TypeScript

AI Engineer AI Modernization Factory-VS Code & TypeScript

InfoVision, Inc.

Irving, TX

Other

Posted 25 days ago


Job description

AI Engineer AI Modernization Factory-VS Code & TypeScript

Role Summary

We are seeking an AI Engineer to design, develop, and evolve the Application AI Modernization Factory an AI-powered platform that automates and accelerates the modernization of large-scale enterprise legacy applications.

This VS Code extension-based solution leverages Large Language Models (LLMs), knowledge graphs, adaptive questioning, and automated code generation to transform legacy Java/Oracle systems into modern architectures such as NSA.

The role involves driving the end-to-end technical vision of the AI Factory from intelligent source code analysis to automated artifact generation while collaborating closely with modernization teams, platform engineers, and AI specialists to continuously improve throughput, accuracy, and coverage.

Key Responsibilities

1. GenAI Engineering

  • Implement a prompt engineering system using structured YAML and Markdown templates, including:
  • Dynamic placeholder substitution
  • Priority filtering
  • Category-based routing
  • Multi-instance LightRAG targeting
  • Build and enhance the Adaptive Questioning Framework, featuring:
  • LLM-driven recursive questioning
  • Configurable probing depth and levels
  • SQL indirection detection
  • Migration-critical validation guarantees
  • Implement and maintain MCP server integrations, including:
  • Vector store operations (upsert, search)
  • Neo4j graph database queries
  • File metadata retrieval

2. Platform Development

  • Design, build, and maintain a VS Code extension (TypeScript/Node.js), including:
  • Chat participant integration
  • Command handlers
  • Guided conversational workflows
  • Design and implement a multi-stage modernization pipeline:
  • Application selection
  • Module-level targeted analysis
  • Adaptive deep-dive questioning
  • LLD (Low-Level Design) generation
  • Code instruction generation
  • Test instruction generation
  • Implementation guidance
  • Develop and evolve a modular extension architecture, including:
  • Services layer: LLM, session, file, user, adaptive questioning
  • Handlers: Chat participant, conversations, APIs, workflows
  • Utilities: Embeddings, token management, error tracking, SQL detection
  • UI components: Buttons, markdown rendering, progress indicators
  • Implement a tiered error-handling framework:
  • Early-stage failure: Stop execution and prompt connectivity diagnostics
  • Mid-stage failure: Pause and auto-retry with exponential backoff
  • Late-stage failure: Continue with partial results
  • Error classification: NETWORK, AUTH, SERVER, TIMEOUT, UNKNOWN
  • Maintain build and packaging pipelines, including:
  • TypeScript strict compilation
  • Bundling
  • Automated VSIX packaging
  • Integrate the VS Code extension with LightRAG services, including:
  • Connection lifecycle management
  • Endpoint targeting and routing
  • Contextual retrieval of legacy code artifacts
  • Collaborate with:
  • LightRAG platform teams on ingestion pipelines and retrieval quality
  • AI engineering peers on shared architecture and enhancements

3. Python Services

  • Maintain Python-based services for vector operations, including:
  • Cosine similarity
  • Batch similarity computation
  • JSON-based TypeScript Python subprocess interoperability
  • Automatic TypeScript fallback on failures
  • Manage embedding pipelines, including:
  • External embedding API integrations
  • Batch processing
  • Exponential backoff retry strategies
  • Configurable batching

What You ll Work On

  • Prompt Engineering System
  • YAML/Markdown-based prompt loader with dynamic filtering, substitutions, and routing
  • AI Chat Agent
  • VS Code chat participant enabling guided modernization workflows
  • Adaptive Questioning Engine
  • Recursive LLM-driven analysis with depth control and migration enforcement
  • Knowledge Graph Integration
  • LightRAG + Neo4j pipeline for context-aware analysis
  • Artifact Generation Pipeline
  • Automated generation of:
  • Low-Level Designs (LLD)
  • Code instructions
  • Test instructions
  • MCP Server & Tools
  • Integration with vector stores, graph databases, and file metadata services
  • Late Chunking & Embedding
  • Efficient semantic retrieval to optimize token usage
  • Python Vector Services
  • High-performance similarity and embedding computation

Technical Skills

Languages: TypeScript, Python, SQL

Runtime: Node.js, Python

GenAI & AI Systems:

  • Prompt engineering
  • Token optimization
  • Multi-model orchestration
  • Retrieval-Augmented Generation (RAG)
  • Model Context Protocol (MCP)

Platform Development:

  • VS Code Extension Development
  • VS Code APIs & Chat Participant API
  • Language Model API integration
  • VSIX packaging

Data Formats:

  • YAML
  • Markdown
  • JSON